验证数字孪生地形模型，提升无人机真实飞行可信度

With the increasing deployment of small Unmanned Aircraft Systems (sUAS) in unfamiliar and complex environments, Environmental Digital Twins (EDT) that comprise weather, airspace, and terrain data are critical for safe flight planning and for maintaining appropriate altitudes during search and surveillance operations. With the expansion of sUAS capabilities through edge and cloud computing, accurate EDT are also vital for advanced sUAS capabilities, like geolocation. However, real-world sUAS deployment introduces significant sources of uncertainty, necessitating a robust validation process for EDT components. This paper focuses on the validation of terrain models, one of the key components of an EDT, for real-world sUAS tasks. These models are constructed by fusing U.S. Geological Survey (USGS) datasets and satellite imagery, incorporating high-resolution environmental data to support mission tasks. Validating both the terrain models and their operational use by sUAS under real-world conditions presents significant challenges, including limited data granularity, terrain discontinuities, GPS and sensor inaccuracies, visual detection uncertainties, as well as onboard resources and timing constraints. We propose a 3-Dimensions validation process grounded in software engineering principles, following a workflow across granularity of tests, simulation to real world, and the analysis of simple to edge conditions. We demonstrate our approach using a multi-sUAS platform equipped with a Terrain-Aware Digital Shadow.